Particle filtering with multiple cues for object tracking in video sequences

Paul A. Brasnett; Lyudmila Mihaylova; Nishan Canagarajah; David Bull

doi:10.1117/12.585882

14 March 2005 Particle filtering with multiple cues for object tracking in video sequences

Paul A. Brasnett, Lyudmila Mihaylova, Nishan Canagarajah, David Bull

Proceedings Volume 5685, Image and Video Communications and Processing 2005; (2005) https://doi.org/10.1117/12.585882
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

In this paper we investigate object tracking in video sequences by using the potential of particle filtering to process features from video frames. A particle filter (PF) and a Gaussian sum particle filter (GSPF) are developed based upon multiple information cues, namely colour and texture, which are described with highly nonlinear models. The algorithms rely on likelihood factorisation as a product of the likelihoods of the cues. We demonstrate the advantages of tracking with multiple independent complementary cues compared to tracking with individual cues. The advantages are increased robustness and improved accuracy. The performance of the two filters is investigated and validated over both synthetic and natural video sequences.

Citation Download Citation

Paul A. Brasnett, Lyudmila Mihaylova, Nishan Canagarajah, and David Bull "Particle filtering with multiple cues for object tracking in video sequences", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); https://doi.org/10.1117/12.585882

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available